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2nd IEEE International Conference on Cloud computing technology and Science, CloudCom 2010

作者： Ibrahim, Shadi Jin, Hai Lu, Lu Wu, Song He, Bingsheng Qi, Li Cluster and Grid Computing Lab Services Computing Technology and System Lab Huazhong University of Science and Technology Wuhan 430074 China School of Computer Engineering Nanyang Technological University Singapore 639798 Singapore Information and Technology Department China Development Bank Beijing 100037 China

ISBN: (纸本)9780769543024

This paper investigates the problem of Partitioning Skew1 in MapReduce-based system. Our studies with Hadoop, a widely used MapReduce implementation, demonstrate that the presence of partitioning skew causes a huge amount of data transfer during the shuffle phase and leads to significant unfairness on the reduce input among different data nodes. As a result, the applications experience performance degradation due to the long data transfer during the shuffle phase along with the computation skew, particularly in reduce phase. We develop a novel algorithm named LEEN for locality-aware and fairness-aware key partitioning in MapReduce. LEEN embraces an asynchronous map and reduce scheme. All buffered intermediate keys are partitioned according to their frequencies and the fairness of the expected data distribution after the shuffle phase. We have integrated LEEN into Hadoop-0.18.0. Our experiments demonstrate that LEEN can efficiently achieve higher locality and reduce the amount of shuffled data. More importantly, LEEN guarantees fair distribution of the reduce inputs. As a result, LEEN achieves a performance improvement of up to 40% on different workloads. © 2010 IEEE.

关键词： MapReduce

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Container lifecycle-aware scheduling for serverless computing

Container lifecycle-aware scheduling for serverless computin...

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作者： Wu, Song Tao, Zhiheng Fan, Hao Huang, Zhuo Zhang, Xinmin Jin, Hai Yu, Chen Cao, Chun National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China

Elastic scaling in response to changes on demand is a main benefit of serverless computing. When bursty workloads arrive, a serverless platform launches many new containers and initializes function environments (known as cold starts), which incurs significant startup latency. To reduce cold starts, platforms usually pause a container after it serves a request, and reuse this container for subsequent requests. However, this reuse strategy cannot efficiently reduce cold starts because the schedulers are agnostic of container lifecycle. For example, it may ignore soon availab.e containers or evict soon needed containers. We propose a container lifecycle-aware scheduling strategy for serverless computing, CAS. The key idea is to control distribution of requests and determine creation or eviction of containers according to different lifecycle phases of containers. We implement a prototype of CAS on OpenWhisk. Our evaluation shows that CAS reduces 81% cold starts and therefore brings a 63% reduction at 95th percentile latency compared with native scheduling strategy in OpenWhisk when there is worker contention between workloads, and does not add significant performance overhead. © 2021 John Wiley & Sons Ltd.

关键词： Containers

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A nearly optimal distributed algorithm for computing the weighted girth

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Science China(Information Sciences) 2021年第11期64卷 80-94页

作者： Qiang-Sheng HUA Lixiang QIAN Dongxiao YU Xuanhua SHI Hai JIN National Engineering Research Center for Big Data Technology and System/Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and Technology School of Computer Science and Technology Shandong University

computing the weighted girth, which is the sum of weights of edges in the minimum weight cycle,is an important problem in network analysis. The problem for distributively computing girth in unweighted graphs has garnered lots of attention, but there are few studies in weighted graphs. In this paper, we propose a distributed randomized algorithm for computing the weighted girth in weighted graphs with integral edge weights in the range [1, nc], where n is the number of vertices and c is a constant. The algorithm is devised under the standard synchronous CON GE S T model, which limits each vertex can only transfer O（log n） bits information along each incident edge in a round. The upper bound of the algorithm is O（n log2n） rounds. We also prove the lower bound for computing the weighted girth is ?（D + n/log n） where D is the hop diameter of the weighted graph. This means our distributed algorithm is optimal within a factor of O（log3n）.

关键词： distributed algorithms weighted girth \({\cal C}{\cal O}{\cal N}{\cal G}{\cal E}{\cal S}{\cal T}\) model communication complexity round complexity

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grid and Cooperative computing - GCC 2004 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Hai Jin Yi Pan Nong Xiao Jianhua Sun

ISBN: (数字)9783540302087

ISBN: (纸本)9783540235644

Welcome to the proceedings of GCC2004 and the city of Wuhan. grid computing has become a mainstream research area in computer science and the GCC conference has become one of the premier forums for presentation of new and exciting research in all aspectsofgridandcooperativecomputing. Theprogramcommitteeispleasedtopresent the proceedings of the 3rd International Conference on grid and Cooperative Comp- ing (GCC2004), which comprises a collection of excellent technical papers, posters, workshops, and keynote speeches. The papers accepted cover a wide range of exciting topics, including resource grid and service grid, information grid and knowledge grid, grid monitoring,managementand organizationtools, grid portal, grid service, Web s- vices and their QoS, service orchestration, grid middleware and toolkits, software glue technologies, grid security, innovative grid applications, advanced resource reservation andscheduling,performanceevaluationandmodeling,computer-supportedcooperative work, P2P computing, automatic computing, and meta-information management. The conference continues to grow and this year a record total of 581 manuscripts (including workshop submissions) were submitted for consideration. Expecting this growth, the size of the program committee was increased from 50 members for GCC 2003 for 70 in GCC 2004. Relevant differences from previous editions of the conf- ence: it is worth mentioning a signi?cant increase in the number of papers submitted by authors from outside China; and the acceptance rate was much lower than for p- vious GCC conferences. From the 427 papers submitted to the main conference, the program committee selected only 96 regular papers for oral presentation and 62 short papers for poster presentation in the program.

关键词： Theory of Computation Computer Communication Networks Operating systems Software Engineering Information systems Applications (incl. Internet) Information Storage and Retrieval

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Efficient distributed algorithms for holistic aggregation functions on random regular graphs

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Science China(Information Sciences) 2022年第5期65卷 32-50页

作者： Lin JIA Qiang-Sheng HUA Haoqiang FAN Qiuping WANG Hai JIN National Engineering Research Center for Big Data Technology and System/Services Computing Technology and System Lab/Cluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and Technology Institute for Interdisciplinary Information Science Tsinghua University

In this paper, we propose efficient distributed algorithms for three holistic aggregation functions on random regular graphs that are good candidates for network topology in next-generation data *** three holistic aggregation functions include SELECTION（select the k-th largest or smallest element）,DISTINCT（query the count of distinct elements）, MODE（query the most frequent element）. We design three basic techniques — Pre-order Network Partition, Pairwise-independent Random Walk, and Random Permutation Delivery, and devise the algorithms based on the techniques. The round complexity of the distributed SELECTION is Θ（log N） which meets the lower bound where N is the number of nodes and each node holds a numeric element. The round complexity of the distributed DISTINCT and MODE algorithms are O（log3N/log log N） and O（log2N log log N） respectively. All of our results break the lower bounds obtained on general graphs and our distributed algorithms are all based on the CON GE S T model, which restricts each node to send only O（log N） bits on each edge in one round under synchronous communications.

关键词： distributed algorithms holistic aggregation function random regular graph \({\cal C}{\cal O}{\cal N}{\cal G}{\cal E}{\cal S}{\cal T}\) model communication complexity round complexity

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Graph for Science: From API based Programming to Graph Engine based Programming for HPC

arXiv

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arXiv 2023年

作者： Zhang, Yu Wang, Zixiao Zhao, Jin Guo, Yuluo Yu, Hui Huang, Zhiying Shi, Xuanhua Liao, Xiaofei National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab. Cluster and Grid Computing Lab. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

Modern scientific applications predominantly run on large-scale computing platforms, necessitating collab.ration between scientific domain experts and high-performance computing (HPC) experts. While domain experts are often skilled in customizing domain-specific scientific computing routines, which often involves various matrix computations, HPC experts are essential for achieving efficient execution of these computations on large-scale platforms. This process often involves utilizing complex parallel computing libraries tailored to specific matrix computation scenarios. However, the intricate programming procedure and the need for deep understanding in both application domains and HPC poses significant challenges to the widespread adoption of scientific computing. In this research, we observe that matrix computations can be transformed into equivalent graph representations, and that by utilizing graph processing engines, HPC experts can be freed from the burden of implementing efficient scientific computations. Based on this observation, we introduce a graph engine-based scientific computing (Graph for Science) paradigm, which provides a unified graph programming interface, enabling domain experts to promptly implement various types of matrix computations. The proposed paradigm leverages the underlying graph processing engine to achieve efficient execution, eliminating the needs for HPC expertise in programming large-scale scientific applications. We evaluate the performance of the developed graph compute engine for three typical scientific computing routines. Our results demonstrate that the graph engine-based scientific computing paradigm achieves performance comparable to the best-performing implementations based on existing parallel computing libraries and bespoke implementations. Importantly, the paradigm greatly simplifies the development of scientific computations on large-scale platforms, reducing the programming difficulty for scientists and facilitating b

关键词： Application programming interfaces (API)

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Optimizing data shuffling in data-parallel computation by understanding user-defined functions 9

Optimizing data shuffling in data-parallel computation by un...

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9th USENIX Symposium on Networked systems Design and Implementation, NSDI 2012

作者： Zhang, Jiaxing Zhou, Hucheng Chen, Rishan Fan, Xuepeng Guo, Zhenyu Lin, Haoxiang Li, Jack Y. Lin, Wei Zhou, Jingren Zhou, Lidong Microsoft Research Asia China Microsoft Bing United States Peking University China Services Computing Technologyand System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan430074 China Georgia Institute of Technology United States

Map/Reduce style data-parallel computation is characterized by the extensive use of user-defined functions for data processing and relies on data-shuffling stages to prepare data partitions for parallel computation. Instead of treating user-defined functions as "black boxes", we propose to analyze those functions to turn them into "gray boxes" that expose opportunities to optimize data shuffling. We identify useful functional properties for userdefined functions, and propose SUDO, an optimization framework that reasons about data-partition properties, functional properties, and data shuffling. We have assessed this optimization opportunity on over 10,000 dataparallel programs used in production SCOPE clusters, and designed a framework that is incorporated it into the production system. Experiments with real SCOPE programs on real production data have shown that this optimization can save up to 47% in terms of disk and network I/O for shuffling, and up to 48% in terms of cross-pod network traffic. © 2012 by The USENIX Association. All Rights Reserved.

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APPLE: A novel P2P based e-learning environment

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3326卷 52-62页

作者： Jin, Hai Yin, Zuoning Yang, Xudong Wang, Fucheng Ma, Jie Wang, Hao Yin, Jiangpei Cluster and Grid Computing Lab. Huazhong University of Science and Technology Wuhan 430074 China

With the rapid development of information technology, dramatic changes have been taken place in the fundamental ways that people acquire and disseminate knowledge. Various e-Learning systems have been designed to help people take full advantage of the benefit brought by the technology. The newly emerged Peer to Peer (P2P) and grid computing will serve as the key driven forces to bring revolutionary impact on the future society. This paper evaluates the potential contribution of the P2P and grid technology into the e-Learning system and introduces a novel P2P based e-Learning environment, called APPLE. With the help of Gnutella-like P2P network, APPLE provides live broadcasting services to share services of education resources. We build a virtual classroom service based on ***, which exposes the service as a grid service that could be accessed by all the users among the grid. © Springer-Verlag Berlin Heidelberg 2004.

关键词： grid computing

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Honeycomb: A peer-to-peer substrate for on-demand media streaming service

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3358卷 330-339页

作者： Deng, Dafu Jin, Hai Zhang, Chao Chen, Hao Liao, Xiaofei Cluster and Grid Computing Lab. Huazhong University of Science and Technology Wuhan 430074 China

Peer-to-Peer media streaming service has gained tremendous momentum in recent years. However, a number of challenges in Peer-to-Peer media streaming have not been addressed. In this paper, we propose a peer-to-peer substrate for supplying on-demand media streaming service, called Honeycomb, which mainly addresses on the key technical issue of: constructing a locality-aware P2P overlay network with high scalab.lity and manageability. Honeycomb can fully utilize the locality of underlying physical network so that the bandwidth consumption used for the overlay maintenance can be effectively saved and the QoS requirements for delivering media content can be easily satisfied. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Media streaming

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Efficient immunization algorithm for peer-to-peer networks

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3296卷 232-241页

作者： Chen, Hao Jin, Hai Sun, Jianhua Han, Zongfen Cluster and Grid Computing Lab. Huazhong University of Science and Technology Wuhan 430074 China

In this paper, we present a detail study about the immunization of viruses in Peer-to-Peer networks exhibiting power-law degree distributions. By comparing two different immunization strategies (randomized and degree-based), we conclude that it is efficient to immunize the highly connected nodes in order to eradicate viruses from the network. Furthermore, we propose an efficient updating algorithm for global virus database according to the degree-based immunization strategy. © Springer-Verlag 2004.

关键词： Immunization

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